Flowability characterises the internal relation of tourism regional system elements and is the primitive core expression of changes in the complex tourism network relation. By using data process, social network technology, P-DBSCAN density clustering, and Markov transition probability based on Flickr’s geotagged photo data, this paper reveals the spatio-temporal characteristics of tourist flow from two dimensions of time and space with a case example of Suzhou, Wuxi, and Changzhou; further, this study analyses the types of spatial hot zones and flow patterns. The results show that the time sequence period of tourist flow has obvious fluctuation characteristics, and travel time distribution tends to be balanced. The flows and connections inside the Suzhou nodes are relatively high; the cross-city flow characteristics are gradually strengthened. The constraint of flow and distance affect and control the scale and direction of tourist flow, which shows the radioactive characteristics of Suzhou Gusu district as the core to the periphery and Wuxi and Changzhou. The tourist hot spots are divided into central hot zones, sub-central hot zones, general hot zones, and borderline hot zones. The hot zones for tourists’ one-day trips are mainly concentrated in 1-4 AOI; one or two AOIs within one day become the main trajectory pattern
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